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What is hyper-geometic probability?
The hyper-geometric distribution is a discrete probability distribution which is similar (in some respects) to the binomial distribution. Suppose you have a population of N which contains R successes. The Binomial describes the probability of r successes in n draws out on N with replacement.However, in many situations the draw is not replaced. In this case you get the hyper-geometric distribution.The function is given by:Prob(r successes in n draws out of N) = RCr/[N-RCn-r * NCn]With the binomial distribution the probability of success remains constant (=R/N) throughout. With the hypergeometric, the numerator for success reduces by one after each successful outcome whereas the denominator reduces by one whatever the outcome.
Moment generating function of a negative binomial distribution?
[(1 - p)/(1 - pet)]r for t < -ln(p) where p = probability of success in each trial, r = number of failures before success.
What is sampling distribution of a statistic called?
The parent probability distribution from which the statistic was calculated is referred to as f(x) and cumulative distribution function as F(x). The sampling distribution and cumulative distribution of a statistic is commonly referred to as g(y) and G(y) where Y is the random variable representing the statistic. There are numerous other notations.
How can one determine the median from a graph?
The answer depends on what the graph is of: the distribution function or the cumulative distribution function.
Which distribution function has equal mean and variance?
The exponential distribution and the Poisson distribution.
Distinguish between binomial distribution and normal distribution?
Normal distribution is the continuous probability distribution defined by the probability density function. While the binomial distribution is discrete.
What is the history behind normal distribution?
The discovery of the Normal distribution is sometimes attributed to de Moivre, who in 1738 published his results on the coefficients in the binomial expansion of (a + b)n. He calculated results for the mean and spread of the binomial expansion. Although it is now possible to relate his theorem to the Normal approximation of the Binomial Distribution, de Moivre himself, was unable to do so because he was unaware of the the concept of a probability density function.In 1809, while developing the theory concerning the method of least squares he concluded that the only law which worked was to use the normal law of errors.A year later Marquis de Laplace proved the Central Limit Theorem. According to this, no matter what the underlying density functions, the means of repeated samples from a population tended towards a nomal distribution. It was also he who calculated the integral of exp(-t2)dt as being sqrt(pi) which allowed the function to be normalised.
What is geomet?
The hyper-geometric distribution is a discrete probability distribution which is similar (in some respects) to the binomial distribution. Suppose you have a population of N which contains R successes. The Binomial describes the probability of r successes in n draws out on N with replacement.However, in many situations the draw is not replaced. In this case you get the hyper-geometric distribution.The function is given by:Prob(r successes in n draws out of N) = RCr/[N-RCn-r * NCn]With the binomial distribution the probability of success remains constant (=R/N) throughout. With the hypergeometric, the numerator for success reduces by one after each successful outcome whereas the denominator reduces by one whatever the outcome.
What is hyper-geometic probability?
The hyper-geometric distribution is a discrete probability distribution which is similar (in some respects) to the binomial distribution. Suppose you have a population of N which contains R successes. The Binomial describes the probability of r successes in n draws out on N with replacement.However, in many situations the draw is not replaced. In this case you get the hyper-geometric distribution.The function is given by:Prob(r successes in n draws out of N) = RCr/[N-RCn-r * NCn]With the binomial distribution the probability of success remains constant (=R/N) throughout. With the hypergeometric, the numerator for success reduces by one after each successful outcome whereas the denominator reduces by one whatever the outcome.
Moment generating function of a negative binomial distribution?
[(1 - p)/(1 - pet)]r for t < -ln(p) where p = probability of success in each trial, r = number of failures before success.
What is the function assisting distribution in seeds?
distribution'
What is sampling distribution of a statistic called?
The parent probability distribution from which the statistic was calculated is referred to as f(x) and cumulative distribution function as F(x). The sampling distribution and cumulative distribution of a statistic is commonly referred to as g(y) and G(y) where Y is the random variable representing the statistic. There are numerous other notations.
How can one determine the median from a graph?
The answer depends on what the graph is of: the distribution function or the cumulative distribution function.
Which distribution function has equal mean and variance?
The exponential distribution and the Poisson distribution.
Probability distribution function of Hotelling's T-square distribution?
there is no pdf in hottling t sq test there is only mdf or it has multivariate distribution function
Is standard normal distribution a probability distribution function?
Yes.
You can easily identify the x-intercepts of a graph of a quadratic function by writing it as two binomial what?
You can easily identify the x-intercepts of a graph of a quadratic function by writing it as two binomial factors! Source: I am in Algebra 2 Honors!
